Cleerly LABS (v2.0)

K242338

Cleerly, Inc. · cleared 2025-03-07 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd

source quote (p.4)

“Cleerly LABS is a web-based software application that is intended to be used by trained medical professionals as an interactive tool for viewing and analyzing cardiac computed tomography (CT) data for determining the presence and extent of coronary plaques (i.e. atherosclerosis) and stenosis in patients who underwent Coronary Computed Tomography Angiography (CCTA) for evaluation of CAD or suspected CAD.”

Algorithmmachine learning and simple rule-based mathematical calculation components; deep learning methodology

source quote (p.6)

“Cleerly LABS utilizes machine learning and simple rule-based mathematical calculation components which are performed on the backend of the software. The software applies deep learning methodology to identify high quality images, segment and label coronary arteries, and segment lumen and vessel walls.”

Adaptive (vs locked)No

source quote (p.7)

“In addition, the core functions of Cleerly LABS are supported by artificial intelligence, nonadaptive machine learning algorithms for CCTA processing and analysis.”

PCCPFDA source did not state this

Cybersecurity addressedYes

source quote (p.8)

“The device has been designed to meet the requirements associated with ISO 14971, 2019-12, Medical Devices – Application of Risk Management to Medical Devices and AAMI TIR 57:2016, Principles for medical device security – Risk management.”

Validation studies (1)

Bench

sample size not stated

standards: ISO 14971, AAMI TIR 57:2016, DICOM, ANSI AAMI IEC 62304:2005/A1:2016

Reported performance (0 observations)

FDA source did not state a quantitative performance metric — non-reporting is itself the signal.

Each value carries its own analysis unit and task — never compare or pool across devices. Source: 510(k) summary PDF.

Predicate network

Postmarket — what happened after clearance

recalls in product code, 24mo

MAUDE reports in code, 12mo

—

vs code's own 3-yr baseline

drift signals on this device

Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device). Signals are descriptive observables with sources — never a judgment that the device is unsafe or drifting. Snapshot 2026-07-08.

Reimbursement — how devices like this got paid

Not yet tracked — no payment pathway indexed for this clearance (the reimbursement corpus is a growing seed set).